A focus group study of Ontario dairy producer perspectives on neonatal care of male and female calves
Notice bibliographique
Résumé
Providing optimal calf care remains a challenge on many dairy farms and has important implications for the future health, welfare, and productivity of male and female calves. Recent research suggests that male dairy calves receive a lower quality of care early in life than female calves, but further investigation is required to determine the factors that influence this disparity. The objectives of this study were to understand dairy producer perspectives on neonatal calf care practices and explore differences between male and female calf care. Overall, 23 dairy producers in Ontario, Canada, participated in 4 focus groups about calf care practices that were recorded and evaluated qualitatively using thematic analysis. Major barriers for good calf care included lack of knowledge about the best management practices for calf care and the prioritization of farm resources toward the milking herd. Some producers also noted that farm infrastructure (particularly during challenging weather) and employee training were important limitations. The economic cost of providing good neonatal calf care was important primarily for male calves and acted as a motivation or a barrier depending on the producer's beliefs about calf care and how they chose to market their calves. The primary source of knowledge producers used to develop calf care practices was their own experience, although many also relied on dairy-industry advisors, most often veterinarians. Producers were motivated by social norms, along with intrinsic pride and obligation to provide good calf care, and these motives were influenced by their emotional state. Producers expressed beliefs about which aspects of calf care are most important-notably colostrum management-and appreciated simple and economical solutions to calf-rearing challenges. Calf care practices were varied, and we identified a diversity of knowledge, motivations, and barriers to adopting best management practices, which sometimes differed between male and female calves. Some producers said that they did not know what happened to their male calves after they left the farm and tended to prioritize the care of female over male calves in subtle ways, such as less timely provision of colostrum. The infrastructure investment and other costs associated with caring for male calves often limited their care, but producers were still motivated to provide adequate care for male calves. These findings represent potential targets for additional research and intervention strategies to improve calf care practices on dairy farms.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».